Congestion Mitigation in a Distributed Storage System

ABSTRACT

A system comprises a plurality of computing devices that are communicatively coupled via a network and have a file system distributed among them, and comprises one or more file system request buffers residing on one or more of the plurality of computing devices. File system choking management circuitry that resides on one or more of the plurality of computing devices is operable to separately control: a first rate at which a first type of file system requests (e.g., one of data requests, data read requests, data write requests, metadata requests, metadata read requests, and metadata write requests) are fetched from the one or more buffers , and a second rate at which a second type of file system requests (e.g., another of data requests, data read requests, data write requests, metadata requests, metadata read requests, and metadata write requests) are fetched from the one or more buffers.

PRIORITY CLAIM

This application claims priority to the following application(s), eachof which is hereby incorporated herein by reference:

-   U.S. provisional patent application 62/288,106 titled “Congestion    Mitigation in a Distributed Storage System” filed on Jan. 28, 2016.

INCORPORATION BY REFERENCE

Each of the following documents is hereby incorporated herein byreference in its entirety:

-   U.S. patent application Ser. No. 14/789,422 titled “Virtual File    System Supporting Multi-Tiered Storage” and filed on July 1, 2015;

U.S. patent application Ser. No. 14/833,053 titled “Distributed ErasureCoded Virtual File System” and filed on August 22, 2015;

U.S. patent application Ser. No. ______ titled “Resource Monitoring in aDistributed Storage System” (Attorney Docket 60305U502) and filed on thesame date as this application.

BACKGROUND

Limitations and disadvantages of conventional approaches to data storagewill become apparent to one of skill in the art, through comparison ofsuch approaches with some aspects of the present method and system setforth in the remainder of this disclosure with reference to thedrawings.

BRIEF SUMMARY

Methods and systems are provided for congestion mitigation in adistributed storage system substantially as illustrated by and/ordescribed in connection with at least one of the figures, as set forthmore completely in the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates various example configurations of a distributedelectronic storage system in accordance with aspects of this disclosure.

FIG. 2 illustrates various example configurations of a compute node thatuses a distributed electronic storage system in accordance with aspectsof this disclosure.

FIG. 3 illustrates various example configurations of a distributedelectronic storage system node in accordance with aspects of thisdisclosure.

FIG. 4 illustrates various example configurations of a dedicated storagenode in accordance with aspects of this disclosure.

FIG. 5A illustrates an example implementation of a node configured forcongestion mitigation in accordance with aspects of this disclosure.

FIG. 5B is a flowchart illustrating an example process for congestionmitigation performed by the node of FIG. 5A.

FIG. 6 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.

FIG. 7 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.

FIG. 8 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.

FIGS. 9A is a flowchart illustrating an example method of configuringchoking settings based on resource load.

FIGS. 9B-9D illustrate examples of application of the method of FIG. 9A.

FIG. 10 is a block diagram illustrating configuration of a DESS from anon-transitory machine-readable storage.

DETAILED DESCRIPTION

FIG. 1 illustrates various example configurations of a distributedelectronic storage system in accordance with aspects of this disclosure.Shown in FIG. 1 is a local area network (LAN) 102 comprising one or moredistributed electronic storage system (DESS) nodes 120 (indexed byintegers from 1 to J, for j≥1), and optionally comprising (indicated bydashed lines): one or more dedicated storage nodes 106 (indexed byintegers from 1 to M, for M≥1), one or more compute nodes 104 (indexedby integers from 1 to N, for N≥1), and/or an edge router 110 thatconnects the LAN 102 to a remote network 118. The remote network 118optionally comprises one or more storage services 114 (indexed byintegers from 1 to K, for K≥1), and/or one or more dedicated storagenodes 115 (indexed by integers from 1 to L, for L≥1). The nodes of theLAN 102 are communicatively coupled via interconnect 101 (e.g., coppercables, fiber cables, wireless links, switches, bridges, hubs, and/orthe like).

Each compute node 104 _(n) (n an integer, where 1≤n≤N) is a networkedcomputing device (e.g., a server, personal computer, or the like) thatcomprises circuitry for running a variety of client processes (eitherdirectly on an operating system of the node 104 _(n) and/or in one ormore virtual machines/containers running on the device 104 _(n)) and forinterfacing with one or more DESS nodes 120. As used in this disclosure,a “client process” is a process that reads data from storage and/orwrites data to storage in the course of performing its primary function,but whose primary function is not storage-related (i.e., the process isonly concerned that its data is reliably stored and retrievable whenneeded, and not concerned with where, when, or how the data is stored).Example applications which give rise to such processes include: an emailserver application, a web server application, office productivityapplications, customer relationship management (CRM) applications, andenterprise resource planning (ERP) applications, just to name a few.Example configurations of a compute node 104 _(n) are described belowwith reference to FIG. 2 .

Each DESS node 120 _(j) (j an integer, where 1≤j≤J) is a networkedcomputing device (e.g., a server, personal computer, or the like) thatcomprises circuitry for running DESS processes and, optionally, clientprocesses (either directly on an operating system of the device 104 _(n)and/or in one or more virtual machines running in the device 104 _(n)).As used in this disclosure, a “DES S process” is a process thatimplements aspects of one or more of: the DESS driver, the DESS frontend, the DESS back end, and the DESS memory controller described belowin this disclosure (any one or more of which may implement one or morechoking processes, as described below). Example configurations of a DESSnode 120 _(j) are described below with reference to FIG. 3 . Thus, in anexample implementation, resources (e.g., processing and memoryresources) of the DESS node 120 _(j) may be shared among clientprocesses and DESS processes. The processes of the DESS may beconfigured to demand relatively small amounts of the resources tominimize the impact on the performance of the client processes. From theperspective of the client process(es), the interface with the DESS maybe independent of the particular physical machine(s) on which the DESSprocess(es) are running Example configurations of a DESS node 120 _(j)are described below with reference to FIG. 3 .

Each on-premises dedicated storage node 106. (m an integer, where 1≤m<M)is a networked computing device and comprises one or more storagedevices and associated circuitry for making the storage device(s)accessible via the LAN 102. An example configuration of a dedicatedstorage node 106 _(m) is described below with reference to FIG. 4 .

Each storage service 114 _(k) (k an integer, where 1≤k≤K) may be acloud-based service such as Amazon S3, Microsoft Azure, Google Cloud,Rackspace, Amazon Glacier, and Google Nearline.

Each remote dedicated storage node 115 _(l) (l an integer, where 1≤l≤L)may be similar to, or the same as, an on-premises dedicated storage node106. In an example implementation, a remote dedicated storage node 115_(l) may store data in a different format and/or be accessed usingdifferent protocols than an on-premises dedicated storage node 106(e.g., HTTP as opposed to Ethernet-based or RDMA-based protocols).

FIG. 2 illustrates various example configurations of a compute node thatuses a DESS in accordance with aspects of this disclosure. The examplecompute node 104 _(n) comprises hardware 202 that, in turn, comprises aprocessor chipset 204 and a network adaptor 208.

The processor chipset 204 may comprise, for example, an x86-basedchipset comprising a single or multi-core processor system on chip, oneor more RAM ICs, and a platform controller hub IC. The chipset 204 maycomprise one or more bus adaptors of various types for connecting toother components of hardware 202 (e.g., PCIe, USB, SATA, and/or thelike).

The network adaptor 208 may, for example, comprise circuitry forinterfacing to an Ethernet-based and/or RDMA-based network. In anexample implementation, the network adaptor 208 may comprise a processor(e.g., an ARM-based processor) and one or more of the illustratedsoftware components may run on that processor. The network adaptor 208interfaces with other members of the LAN 100 via (wired, wireless, oroptical) link 226. In an example implementation, the network adaptor 208may be integrated with the chipset 204.

Software running on the hardware 202 of compute node 104 _(n) includesat least: an operating system and/or hypervisor 212, one or more clientprocesses 218 (indexed by integers from 1 to Q, for Q≥1) and one or bothof: a DESS driver 221 and DESS front end 220. Additional software thatmay optionally run on the compute node 104 _(n) includes: one or morevirtual machines (VMs) and/or containers 216 (indexed by integers from 1to R, for R≥1).

Each client process 218 _(q) (q an integer, where 1≤q≤Q) may rundirectly on an operating system/hypervisor 212 or may run in a virtualmachine and/or container 216 _(r) (r an integer, where 1≤r≤R) servicedby the OS and/or hypervisor 212.

The DESS driver 221 is operable to receive/intercept local file systemcommands (e.g., POSIX commands) and generate corresponding file systemrequests (e.g., read, write, create, make directory, remove, removedirectory, link, etc.) to be transmitted onto the interconnect 101. Insome instances, the file system requests transmitted on the interconnect101 may be of a format customized for use with the DESS front end 220and/or DESS back end 222 described herein. In some instances, the filesystem requests transmitted on the interconnect 101 may adhere to astandard such as Network File System (NFS), Server Message Block (DMB),Common Internet File System (CIFS), and/or the like.

Each DESS front end instance 220 _(s) (s an integer, where 1≤s≤S if atleast one front end instance is present on compute node 104 _(n))provides an interface for routing file system requests to an appropriateDESS back end instance (running on a DESS node), where the file systemrequests may originate from one or more of the client processes 218, oneor more of the VMs and/or containers 216, and/or the OS and/orhypervisor 212. Each DESS front end instance 220 _(s) may run on theprocessor of chipset 204 or on the processor of the network adaptor 208.For a multi-core processor of chipset 204, different instances of theDESS front end 220 may run on different processing cores.

FIG. 3 shows various example configurations of a distributed electronicstorage system node in accordance with aspects of this disclosure. Theexample DESS node 120 _(j) comprises hardware 302 that, in turn,comprises a processor chipset 304, a network adaptor 308, and,optionally, one or more storage devices 306 (indexed by integers from 1to W, for W≥1).

Each storage device 306 _(p) (p an integer, where 1≤p≤P if at least onestorage device is present) may comprise any suitable storage device forrealizing a tier of storage that it is desired to realize within theDESS node 120 _(j).

The processor chipset 304 may be similar to the chipset 204 describedabove with reference to FIG. 2 . The network adaptor 308 may be similarto the network adaptor 208 described above with reference to FIG. 2 andmay interface with other nodes of LAN 100 via link 326.

Software running on the hardware 302 includes at least: an operatingsystem and/or hypervisor 212, and at least one of: one or more instancesof DESS front end 220 (indexed by integers from 1 to W, for W≥1), one ormore instances of DESS back end 222 (indexed by integers from 1 to X,for X≥1), and one or more instances of DESS memory controller 224(indexed by integers from 1 to Y, for Y≥1). Additional software that mayoptionally run on the hardware 302 includes: one or more virtualmachines (VMs) and/or containers 216 (indexed by integers from 1 to R,for R≥1), and/or one or more client processes 318 (indexed by integersfrom 1 to Q, for Q≥1). As mentioned above, DESS processes and clientprocesses may share resources on a DESS node.

The client processes 218 and VM(s) and/or container(s) 216 are asdescribed above with reference to FIG. 2 .

Each DESS front end instance 220 _(w) (w an integer, where 1≤w≤W, if atleast one front end instance is present on DESS node 120 _(j)) providesan interface for routing file system requests to an appropriate DESSback end instance (running on the same or a different DESS node), wherethe file system requests may originate from one or more of the clientprocesses 218, one or more of the VMs and/or containers 216, and/or theOS and/or hypervisor 212. Each DESS front end instance 220 _(w) may runon the processor of chipset 304 or on the processor of the networkadaptor 308. For a multi-core processor of chipset 304, differentinstances of the DESS front end 220 may run on different processingcores.

Each DESS back end instance 222 _(x) (x an integer, where 1≤x≤X, if atleast one back end instance is present on DESS node 120 _(j)) servicesthe file system requests that it receives and carries out tasks tootherwise manage the DESS (e.g., load balancing, journaling, maintainingmetadata, caching, moving of data between tiers, removing stale data,correcting corrupted data, etc.) Each DESS back end instance 222 _(x)may run on the processor of chipset 304 or on the processor of thenetwork adaptor 308. For a multi-core processor of chipset 304,different instances of the DESS back end 222 may run on differentprocessing cores.

Each DESS memory controller instance 224 _(u) (u an integer, where1≤u≤U, if at least DESS memory controller instance is present on DESSnode 120 _(j)) handles interactions with a respective storage device 306(which may reside in the DESS node 120 j or another DESS node 120 or astorage node 106). This may include, for example, translating addresses,and generating the commands that are issued to the storage device (e.g.,on a SATA, PCIe, or other suitable bus). Thus, the DESS memorycontroller instance 224 _(u) operates as an intermediary between astorage device and the various DESS back end instances of the DESS.

FIG. 4 illustrates various example configurations of a dedicated storagenode in accordance with aspects of this disclosure. The examplededicated storage node 106 _(m) comprises hardware 402 which, in turn,comprises a network adaptor 408 and at least one storage device 306(indexed by integers from 1 to Z, for Z≥1). Each storage device 306 _(z)may be the same as storage device 306 _(w) described above withreference to FIG. 3 . The network adaptor 408 may comprise circuitry(e.g., an arm based processor) and a bus (e.g., SATA, PCIe, or other)adaptor operable to access (read, write, etc.) storage device(s) 406_(l)-406 _(z) in response to commands received over network link 426.The commands may adhere to a standard protocol. For example, thededicated storage node 106 _(m) may support RDMA based protocols (e.g.,Infiniband, RoCE, iWARP etc.) and/or protocols which ride on RDMA (e.g.,NVMe over fabrics).

In an example implementation, tier 1 memory is distributed across one ormore storage devices 306 (e.g., FLASH devices) residing in one or morestorage node(s) 106 and/or one or more DESS node(s) 120. Data written tothe DESS is initially stored to Tier 1 memory and then migrated to oneor more other tier(s) as dictated by data migration policies, which maybe user-defined and/or adaptive based on machine learning.

FIG. 5A illustrates a first example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.The example DESS node 120 _(l) in FIG. 5A is configured to implement aclient process 218, a file system request buffer 504, an instance ofDESS front end 220, an instance of DESS backend 222, a storage device306 comprising a buffer 502, and one or more file system chokingprocess(es) 506.

The client process 218 may be as described above with reference to FIGS.1-4 . The client process 218 submits file system requests to the DESSand those file system requests are buffered in file system requestbuffer 504.

The file system request buffer 504 may, for example, reside in memory ofthe chipset 204 (FIG. 2 ) or 304 (FIG. 3 ). In the exampleimplementation shown, the node 102 _(i) comprises only a single buffer504. In an example implementation in which the DESS comprises aplurality of distributed file systems which are mounted on the node 120_(l), the node 120 _(l) may comprise a plurality of buffers 504—one foreach of the mounted file systems.

The buffer 502 may, for example, comprise RAM within the storage device306 _(v). The buffer 502 is used for buffering data being read fromand/or written to nonvolatile storage (e.g., FLASH) of the storagedevice 306.

The file system choking process(es) 506 control the rate at which thefile system requests in the buffer 504 are fetched by the front end 220so as to manage congestion in (and, thus, quality of service providedby) the DESS.

In operation, the front end fetches batches of file system requests fromthe buffer 504, determines which back end instance(s) 222 should servicethe request(s), generates the appropriate DESS message(s) for conveyingthe request(s) to the back end(s) 222, and transmits DESS message(s) tothe determined back end(s) 222 via the network 102. The back end(s) 222receive the DESS message(s) and perform the necessary operations tocarry out the file system request (typically involving reading and/orwriting data and/or metadata from/to one or more storage device(s) 306).The rate at which the file system requests are fetched from the buffer504 is controlled by the choking process(es) 506. In an exampleimplementation (further described below with reference to FIGS. 9A-9D),this comprises the choking process(es) 506 determining a choking leveland then adjusting one or more settings based on the determined chokinglevel. The one or more settings may comprise, for example: a batchtiming setting (i.e., the timing of when file system requests arefetched from the buffer 504), and a batch size setting (i.e., how filesystem requests are fetched from the buffer 504 at a time). The batchtiming setting may, for example, be an interval duration and/or anoffset relative to some reference time.

The control of the rate at which file system requests are fetched may bebased on information about the state of the DESS. The state informationmay be based on the load on (i.e., level of usage of) resources of theDESS. The load may be a most-recently measured/recorded load or may be apredicted load based on historical measurement/recordings (for the sameDESS and/or other DESSs) being input to a prediction algorithm Suchresources may include resources of the node 120 _(l) (DESS resources“local” to node 120 _(l)). Such resources may also include similarresources of other nodes 104, 120 _(j), and/or 106 of the DESS (DES Sresources that are “remote” from the perspective of node 120 _(l)).Information about the loads on remote resources may be determined fromDESS messages received from other nodes of the DESS. Similarly, the node120 _(l) may transmit DESS messages which indicate the loads on itsresources. Such DESS messages may contain a direct representation ofload on one or more resources and/or may contain values calculated basedon the load no one or more resources. Examples of such values calculatedbased on the resource load values are described below with reference toFIGS. 9A-9D. This bidirectional exchange of choking information giveschoking processes 506 throughout the DESS a more holistic view of thestate of the DESS, which enables them to more optimally control the rateat which they submit file system requests to the DESS as compared to ifthey had to control the rate based only on their respective localresource loads.

Resources for which resource load may be monitored include one or moreof the following: storage device, CPU, network, and memory. A load on astorage device may, for example, be represented by a single valuedetermined from depth of buffer 502, or represented by two values wherethe first is determined from depth of read buffer 710 and the second isdetermined from depth of write buffer 712. A load on a CPU may, forexample, be represented by a value corresponding to a running average ofpercentage of available cycles per second being used. A load on anetwork adaptor or link may, for example, be represented by a singlevalue determined from depth of transmit and/or receive buffers, orrepresented by two values where the first is determined from depth of atransmit buffer and the second is determined from depth of a receivebuffer. A load on a memory may, for example, be represented by a singlevalue determined from the amount of used (or free) memory.

Details of example operation of the implementation of FIG. 5A will nowbe described with reference to the flowchart of FIG. 5B.

The process of FIG. 5B begins with block 552 in which the DESS beginsits startup/initialization process (e.g., after power up or reset of thenode(s) across which it is distributed).

In block 554, various resources (e.g., CPU(s), memory, networkadaptor(s), and storage device(s)) of the DESS are characterized. Forexample, a choking process 506 on each node of the DESS may determine(e.g., through one or more commands supported by the node's operatingsystem) the identity (e.g., manufacturer, model number, serial number,and/or the like) of local resources, and use those identities toretrieve corresponding characteristics from a resource characteristicsdatabase (e.g., stored locally in the network 102 and/or accessible viathe Internet). For a resource such as a CPU, such characteristics mayinclude, for example, clock speed, cache size, cache speed, number ofcores, and/or the like. For a resource such as memory, suchcharacteristics may include, for example, size of memory, speed ofmemory, and/or the like. For a network adaptor such characteristics mayinclude, for example, latency, maximum throughput, buffer size, and/orthe like. For a resource such as a storage device such characteristicsmay include, for example, size of its buffer 502, write speed (e.g., ininput/output operations per second (IOPS)) as a function of the depth(i.e., fill level) of its buffer 502, read speed as a function of thedepth of its buffer 502, and/or the like. In instances that a record isnot found in the database for an identified resource, a choking process506 may perform a characterization of the resource before proceeding toblock 556. As an example, test reads and/or writes may be issued to astorage device 306 and the resulting read and/or write speed as afunction of the depth of its buffer 502 may be monitored and then usedto generate a characterization which is then stored to the database.

In block 555, one or more settings used by the choking process(es) 506are configured based on the resource characteristics determined in block554. As an example (further described below with reference to FIGS.9A-9D), one or more functions may be used for mapping resource loadvalues to congestion contribution values, mapping congestioncontribution values to a choking level, and mapping a choking level tovalues for a batch timing setting and a batch size setting. Suchfunction(s) may have one or more parameters which may be set based onthe characteristics determined in block 554.

In block 556, each node of the DESS determines its initial chokingsettings (e.g., initial batch timing and batch size settings). Theinitial choking settings may, for example, be set empirically by a DESSadministrator and/or may be set automatically by the choking process 506based on historical settings used in this DESS and/or other DESSs (e.g.,as adapted by a learning algorithm)

In block 557, the DESS is ready to begin servicing file system requests.

In block 558, a front end 220 of a DESS node 120 _(j) (Note: the node120 _(j) may be a different node on different iterations through theloop comprising blocks 558-566) fetches file system request(s) from itsbuffer 504 based on its choking settings (e.g., values of batch timingand batch size), and generates one or more corresponding DESS message(s)(e.g., message(s) to convey the file system requests to the appropriateback end(s) 222).

In block 560, a choking process 506 of the node 120 _(j) inserts chokinginformation into the DESS message(s).

In block 562, the node 120 _(j) transmits the DESS message(s) into thenetwork 102.

In block 564, other node(s) of the DESS receive the DESS message(s) andextract(s) the choking information.

In block 566, the other node(s) update their choking settings based onthe choking information from node 120 _(j) and based on theirmost-recent load information for other resources.

FIG. 6 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.FIG. 6 is largely the same as FIG. 5A except the node 120 _(j) in FIG. 6manages different types of file system requests separately.Specifically, file system requests which require reading and/or writingdata to/from the distributed file system are managed separately fromfile system requests which require reading and/or writing metadatato/from the distributed file system. The separate management may berealized, for example, using two separate FIFO buffers 602 and 604 asshown, but may also be realized in other ways such as using a singlerandom access buffer.

In the example implementation shown, the node 102 _(j) comprises only asingle buffer 602 and a single buffer 604. In an example implementationin which the DESS comprises a plurality of distributed file systemswhich are mounted on the node 120 _(j), the node 120 _(j) may comprise aplurality of buffers 602 (one for each file system of the DESS mountedon node 120 _(j)) and a plurality of buffers 604 (one for each filesystem of the DESS mounted on node 120 _(j)).

Operation of the example node 120 _(j) of FIG. 6 is similar to asdescribed with reference to FIG. 5A, with the rate at which requests arefetched from buffer 602 being controlled separately from rate at whichrequests are fetched from buffer 604. For example, choking process(es)506 of node 120 _(j) may control the rate at which file system datarequests are fetched from buffer 602 by controlling a data batch timingsetting (T_(D)) and a data batch size setting (S_(D)), and may controlthe rate at which file system metadata requests are fetched from buffer604 by controlling a metadata batch timing setting (T_(M)) and ametadata batch size setting (S_(M)). The ability to separately controlthe rate of file system data requests and file system metadata requestsis advantageous at least because, in many cases, file system metadatarequests are more important than file system data requests because filesystem metadata requests enable, for example: querying the status of theDESS; making some changes so to optimize in-process file systemoperations. Further, metadata requests are often run by interactive“human generated” sessions, so getting them to execute quicker resultsin a higher level of user satisfaction. Accordingly, in some instanceswhen the DESS is getting congested, the choking process(es) 506 mayreduce the rate at which requests are fetched from buffer 602 soonerand/or more aggressively than the rate at which requests are fetchedfrom buffer 604. In some instances this may lead to a scenario in whichfile system metadata requests, but not file system data requests, arefetched during a determined time interval.

FIG. 7 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.FIG. 7 is largely the same as FIG. 6 except, in FIG. 7 , the separatemanagement is of file system read requests and file system writerequests, rather than of file system data requests and file systemmetadata requests. The separate management may be realized, for example,using two separate FIFO buffers 702 and 704 as shown, but may also berealized in other ways such as using a single random access buffer.

In the example implementation shown, the node 102 _(i) comprises only asingle buffer 702 and a single buffer 704. In an example implementationin which the DESS comprises a plurality of distributed file systemswhich are mounted on the node 120 _(l), the node 120 _(l) may comprise aplurality of buffers 702 (one for each file system of the DESS mountedon node 120 _(j)) and a plurality of buffers 704 (one for each filesystem of the DESS mounted on node 120 _(j)).

Operation of the example node 120 _(j) of FIG. 7 is similar to asdescribed with reference to FIG. 6 , with the rate at which requests arefetched from buffer 702 being controlled separately from chokingsettings for buffer 704. For example, choking process(es) 506 of node120 _(j) may control the rate at which file system data write requestsare fetched from buffer 702 by separately controlling a write timingsetting (T_(W)), a write batch size setting (S_(W)), a read timingsetting (T_(R)), a read batch size setting (S_(R)), metadata batchtiming setting (T_(M)), and a metadata batch size setting (S_(M)). Theability to separately control the rate of file system read requests andfile system write requests is advantageous at least because, forexample, write operations and read operations may use differentresources which may become congested at different rates. For example, itmay occur at some particular time that there are many read operationspending and thus buffer 710 of storage device 306 cannot accept any moreread requests, but buffer 712 has capacity to accept write requests (andresources of the storage device 306 are available to begin working onsuch write requests). Without separate management of file system readrequests and file system write requests, write requests in the buffer504 (FIG. 5 ) may be blocked by read requests waiting for resources instorage device 306 to free up. Similarly, it may occur at someparticular time that there are many write operations pending and thusbuffer 712 of storage device 306 cannot accept any more write requests,but buffer 710 has capacity to accept read requests (and resources ofthe storage device 306 are available to begin working on such readrequests). Without separate management of file system read requests andfile system write requests, read requests in the buffer 504 (FIG. 5 )may be blocked by read requests waiting for resources in storage device306 to free up. The implementation of FIG. 7 avoids this problem andpermits the DESS to begin working on one or more pending write requests.

FIG. 8 illustrates another example implementation of a node configuredfor congestion mitigation in accordance with aspects of this disclosure.FIG. 8 can be viewed as a combination of FIGS. 6 and 7 .

FIGS. 9A is a flowchart illustrating an example method of configuringchoking settings based on resource load. The process begins in block 902in which node 102 _(j) determines the load on one or more local and/orremote resources of the DESS. As described above, this may include eachnode determining the load on its local resources (this may be a currentmeasurement/estimation or prediction for some time in the future) andincluding this information (or derivatives thereof) in DESS messagessent to other nodes. The resource loads may, for example, be representedas a numerical value (e.g., on a scale of 0 to 7, using 3 bits).

In block 904, the node 102 _(j) maps the individual load values for eachresource to a composite load value using a first function. For example,in FIGS. 9B-9D, the node 102 _(j) may generate a CPU load value, amemory load value, a storage device load value, and a network loadvalue; and may also receive one or more CPU load values, one or morememory load values, one or more storage device load values, and one ormore network load values from other nodes of the DESS. The node 102 _(j)may then maps the two or more CPU load values to a composite CPU loadvalue, the two or more memory load values to a composite memory loadvalue, the two or more storage device load values to a composite storagedevice load value, and the two or more network load values to acomposite network load value. The first function may be, for example, asum, an average, a weighted average (e.g., load values determined morerecently given more weight than older values), or any other suitablefunction. These composite load values are shown along the X axis inFIGS. 9B-9D.

In block 906, the node 102 _(j) maps each composite resource load valueto a corresponding congestion contribution values using a secondfunction. Any suitable function may be used. In the exampleimplementations illustrated in FIGS. 9B-9D, the second function is thefollowing piecewise linear function:

$y = \left\{ \begin{matrix}{0,{{{for}x} < A}} \\{{m_{1} \cdot \left( {x - A} \right)},{{{for}A} \leq x \leq B}} \\{{{m_{2} \cdot \left( {x - B} \right)} + {m_{1} \cdot \left( {x - \left( {B - A} \right)} \right)}},{{{for}x} > B}}\end{matrix} \right.$

One or more of the variables m1, m2, A, and B may be determined (e.g.,preset by a DESS administrator and/or adapted using a learningalgorithm) based on the determined type (e.g., CPU, memory, network, andstorage device) of DESS resources. Although the same function is shownas applying to all of the composite load values, this need not be thecase. For example, one or more of the variables may take on firstvalue(s) (which may vary based on determined characteristics as, forexample, described above with reference to FIGS. 5A and 5B) when mappingthe composite network load value and second value(s) (which may varybased on determined characteristics as, for example, described abovewith reference to FIGS. 5A and 5B) when mapping the composite storagedevice load value.

One or more of the variables m1, m2, A, and B may be determined based oncharacteristics of DESS resources (and may vary over time as thecharacteristics vary). For example, one or more of the variables maytake on first value(s) for a first file system distributed acrossstorage device(s) 306 having first characteristics and second value(s)for a second file system distributed across storage device(s) 306 havingsecond characteristics. As another example, the variables may adapt overtime as the resources age (e.g., as a storage device ages itscharacteristics may change).

In block 908, the congestion contributions are mapped to a choking levelusing a third function. The third function may be, for example, a sum,an average, a weighted average, or any other suitable function. In theexample implementation of FIGS. 9B-9D, the third function is the sum ofthe congestion contribution levels. The third function may be determinedbased on characteristics of DESS resources and may adapt as thecharacteristics change over time.

In block 910, the congestion settings, such as one or more batch timingsettings and/or one or more batch size settings, are configured based onthe determined congestion level. For example, congestion level may bemapped to such settings using a lookup table or one or more fourthfunctions. The lookup table or fourth function(s) may be set by a DESSadministrator and/or adapt based on a learning algorithm (e.g., setand/or adapted based on DESS characteristics and/or changes in thecharacteristics over time).

In various example implementations, changes to choking settings, changesto function variables, and/or changes to any other configuration changesmay be limited by hysteresis settings (which themselves may beuser-defined and/or adaptive) and/or may updated in a moving averagefashion so as to reduce jitter, oscillations, etc. in the values.

FIG. 10 is a block diagram illustrating configuration of a DESS from anon-transitory machine-readable storage media. Shown in FIG. 10 isnon-transitory storage 1002 on which resides code 1003. The code is madeavailable to computing devices 1004 and 1006 (which may be computenodes, DESS nodes, and/or dedicated storage nodes such as thosediscussed above) as indicated by arrows 1010 and 1012. For example,storage 1002 may comprise one or more electronically addressed and/ormechanically addressed storage devices residing on one or more serversaccessible via the Internet and the code 1003 may be downloaded to thedevices 1004 and 1006. As another example, storage 1002 may be anoptical disk or FLASH-based disk which can be connected to the computingdevices 1004 and 1006 (e.g., via USB, SATA, PCIe, and/or the like).

When executed by a computing device such as 1004 and 1006, the code 1003may install and/or initialize one or more of the DESS driver, DESSfront-end, DESS back-end, DESS memory controller on the computingdevice. This may comprise copying some or all of the code 1003 intolocal storage and/or memory of the computing device(s) 1004 and/or 1006and beginning to execute the code 1003 (launching one or more DESSprocesses) by one or more processors of the computing device(s) 1004and/or 1006. Which of code corresponding to the DESS driver, codecorresponding to the DESS front-end, code corresponding to the DESSback-end, and/or code corresponding to the DESS memory controller iscopied to local storage and/or memory of the computing device(s) 1004and/or 1006 and is executed by the computing device(s) 1004 and/or 1006may be configured by a user during execution of the code 1003 and/or byselecting which portion(s) of the code 1003 to copy and/or launch. Inthe example shown, execution of the code 1003 by the device 1004 hasresulted in one or more client processes and one or more DESS processesbeing launched on the processor chipset 1014. That is, resources(processor cycles, memory, etc.) of the processor chipset 1014 areshared among the client processes and the DESS processes. On the otherhand, execution of the code 1003 by the device 1006 has resulted in oneor more DESS processes launching on the processor chipset 1016 and oneor more client processes launching on the processor chipset 1018. Inthis manner, the client processes do not have to share resources of theprocessor chipset 1016 with the DESS process(es). The processor chipset1018 may comprise, for example, a process of a network adaptor of thedevice 1006.

In accordance with an example implementation of this disclosure, asystem comprises a plurality of computing devices (e.g., 120 _(l)-120_(j)) that are communicatively coupled via one or more network links(e.g., 101) and have a file system distributed among them. One or morefile system request buffers (e.g., 504, 602, 604, 702, 704, 802, 804,806, and/or 808) reside on one or more of the plurality of computingdevices. File system choking management circuitry (e.g., hardware 302configured by an OS 312, a DESS front end instance 220, and a chokingprocess 506) that resides on one or more of the plurality of computingdevices and is operable to separately control: a first rate at which afirst type of file system requests (e.g., one of data requests, dataread requests, data write requests, metadata requests, metadata readrequests, and metadata write requests) in the one or more buffers arefetched by the file system, and a second rate at which a second type offile system requests (e.g., another of data requests, data readrequests, data write requests, metadata requests, metadata readrequests, and metadata write requests) are fetched from the one or morebuffers. The control of the first rate may comprise an adjustment of afirst batch timing setting (e.g., one of data batch timing setting, dataread batch timing setting, data write batch timing setting, metadatabatch timing setting, metadata read batch timing setting, and metadatawrite batch timing setting) and/or a first batch size setting (e.g., oneof data batch size, data read batch size, data write batch size,metadata batch size, metadata read batch size, and metadata write batchsize). The control of the second rate comprises an adjustment of asecond batch timing setting (e.g., another of data batch timing setting,data read batch timing setting, data write batch timing setting,metadata batch timing setting, metadata read batch timing setting, andmetadata write batch timing setting) and/or a second batch size setting(e.g., another of data batch size, data read batch size, data writebatch size, metadata batch size, metadata read batch size, and metadatawrite batch size). The first type of file system requests may berequests to read data (and not write data nor read or write metadata)from the file system and/or write data (and not read data nor not reador write metadata) to the file system, and the second type of filesystem requests may be requests to read metadata (and not write metadatanor read or write data) from the file system and/or write metadata (andnot read metadata nor read or write data) to the file system. The filesystem choking management circuitry may be operable to control,separately from the first rate and the second rate, a third rate atwhich a third type of file system requests in the one or more buffersare serviced by the file system. The control may be based on currentand/or predicted load on one or more resources of the plurality ofcomputing devices. The one or more resources may comprise a storagedevice (e.g., 306); and the current and/or predicted load may be basedon a depth of a buffer (e.g., 502) of the storage device. The filesystem choking management circuitry may be operable to calculate achoking level based on current and/or predicted load on one or moreresources of the plurality of computing devices. The control of thefirst rate and of the second rate may be based on the choking level. Thecalculation of the choking level may comprises a mapping, according to afirst determined function, of a plurality of resource load values forresources of the plurality of computing devices to a plurality ofcongestion contribution values. The plurality of resource load valuescomprise two or more of: a network load value; a processing core loadvalue; a memory load value; and a storage device load value. Theplurality of resource load values comprises a storage device read loadvalue (e.g. SD_R load, FIG. 9C) and a storage device write load value(e.g. SD_W load, FIG. 9C). The resources of the plurality of computingdevices may comprise a storage device (e.g., 306) which stores dataand/or metadata of the file system, and the first determined functionmay be determined based on characteristics of the storage device (e.g.,the determination of variables of the piecewise linear function of FIGS.9B-9D). The system of claim 17, wherein the characteristics of thestorage device are determined from one or more of: a manufacturer of thestorage device; a manufacturer of a component of the storage device; amodel of the storage device; a model of a component of the storagedevice; a serial number of the storage device; and a serial number of acomponent of the storage device. The characteristics of the storagedevice may comprise inputs/outputs per second as a function of bufferdepth. The calculation of the choking level may comprises a combining ofthe plurality of congestion contribution values according to a seconddetermined function (e.g., the summing y_(CPU), y_(MEM), y_(SD), andy_(NET) in FIG. 9B).

Thus, the present methods and systems may be realized in hardware,software, or a combination of hardware and software. The present methodsand/or systems may be realized in a centralized fashion in at least onecomputing system, or in a distributed fashion where different elementsare spread across several interconnected computing systems. Any kind ofcomputing system or other apparatus adapted for carrying out the methodsdescribed herein is suited. A typical combination of hardware andsoftware may be a general-purpose computing system with a program orother code that, when being loaded and executed, controls the computingsystem such that it carries out the methods described herein. Anothertypical implementation may comprise an application specific integratedcircuit or chip. Some implementations may comprise a non-transitorymachine-readable storage medium (e.g., FLASH drive(s), optical disk(s),magnetic storage disk(s), and/or the like) having stored thereon one ormore lines of code executable by a computing device, thereby configuringthe machine to be configured to implement one or more aspects of themethods and systems described herein.

While the present method and/or system has been described with referenceto certain implementations, it will be understood by those skilled inthe art that various changes may be made and equivalents may besubstituted without departing from the scope of the present methodand/or system. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the presentdisclosure without departing from its scope. Therefore, it is intendedthat the present method and/or system not be limited to the particularimplementations disclosed, but that the present method and/or systemwill include all implementations falling within the scope of theappended claims.

As utilized herein the terms “circuits” and “circuitry” refer tophysical electronic components (i.e. hardware) and any software and/orfirmware (“code”) which may configure the hardware, be executed by thehardware, and or otherwise be associated with the hardware. As usedherein, for example, a particular processor and memory may comprisefirst “circuitry” when executing a first one or more lines of code andmay comprise second “circuitry” when executing a second one or morelines of code. As utilized herein, “and/or” means any one or more of theitems in the list joined by “and/or”. As an example, “x and/or y” meansany element of the three-element set {(x), (y), (x, y)}. In other words,“x and/or y” means “one or both of x and y”. As another example, “x, y,and/or z” means any element of the seven-element set {(x), (y), (z), (x,y), (x, z), (y, z), (x, y, z)}. In other words, “x, y and/or z” means“one or more of x, y and z”. As utilized herein, the term “exemplary”means serving as a non-limiting example, instance, or illustration. Asutilized herein, the terms “e.g.,” and “for example” set off lists ofone or more non-limiting examples, instances, or illustrations. Asutilized herein, circuitry is “operable” to perform a function wheneverthe circuitry comprises the necessary hardware and code (if any isnecessary) to perform the function, regardless of whether performance ofthe function is disabled or not enabled (e.g., by a user-configurablesetting, factory trim, etc.).

What is claimed is: 1-23. (canceled)
 24. A distributed storage system(DSS) comprising: a rate controller circuit; a local computing device; aplurality of remote computing devices; and a network, wherein: the ratecontroller circuit to manage choking in the DSS, the local computingdevice is associated with a request buffer, the network communicativelycouples the local computing device to the plurality of remote computingdevices, the rate controller to control, according to a batch size, afirst rate at which a first type of requests are fetched from therequest buffer, and the rate controller to control a second rate atwhich a second type of requests are fetched from the request buffer. 25.The DSS of claim 24, wherein rate controller circuit is operable tocontrol the first rate according to a batch timing.
 26. The DSS of claim25, wherein the rate controller circuit is operable to adjust a batchtiming setting and a batch size setting.
 27. The DSS of claim 24,wherein: the first type of requests comprise requests to read data fromthe system and requests to write data to the DSS; and the second type ofrequests comprise requests to read metadata from the system and requeststo write metadata to the DSS.
 28. The DSS of claim 24, wherein the ratecontroller circuit is operable to adjust: a data batch timing setting; adata batch size setting; a metadata batch timing setting; and a metadatabatch size setting.
 29. The DSS of claim 24, wherein: the first type ofrequests comprise requests to read data from the DSS and requests toread metadata from the DSS; and the second type of requests compriserequests to write data to the DSS and requests to write metadata to theDSS.
 30. The DSS of claim 24, wherein the rate controller circuit isoperable to adjust: a read batch timing setting; a read batch sizesetting; a write batch timing setting; and a write batch size setting.31. The DSS of claim 24, wherein the rate controller circuit is operableto control, independently from the first rate and the second rate, athird rate at which a third type of requests are fetched from one ormore buffers.
 32. The DSS of claim 24, wherein the rate controllercircuit is operable to adjust: a data read batch timing setting; a dataread batch size setting; a data write batch timing setting; a data writebatch size setting; a metadata batch timing setting; and a metadatabatch size setting.
 33. The DSS of claim 24, wherein the rate controllercircuit is operable to control according to a current load on one ormore resources of the local computing device and according to apredicted load on one or more resources of the plurality of remotecomputing devices.
 34. The DSS of claim 33, wherein: the one or moreresources comprise a storage device; and a load on one or more resourcesof the plurality of remote computing devices is based on a depth of abuffer of the storage device.
 35. The DSS of claim 24, wherein: the ratecontroller circuit is operable to calculate a choking level based on acurrent load and a predicted load on one or more resources of theplurality of remote computing devices; and the control of the first rateand of the second rate is based on the choking level.
 36. The DSS ofclaim 35, wherein the calculation of the choking level comprises amapping, according to a first determined function, of a plurality ofresource load values for resources of the plurality of remote computingdevices to a plurality of congestion contribution values.
 37. The DSS ofclaim 36, wherein the plurality of resource load values comprise two ormore of: a network load value; a processing core load value; a memoryload value; and a storage device load value.
 38. The DSS of claim 37,wherein the storage device load value is determined based on a depth ofa buffer of a storage device of the plurality of remote computingdevices.
 39. The DSS of claim 36, wherein the plurality of resource loadvalues comprises a storage device read load value and a storage devicewrite load value.
 40. The DSS of claim 36 wherein: the resources of theplurality of remote computing devices comprise a storage device whichstores data and/or metadata of the DSS; and the first determinedfunction is determined based on characteristics of the storage device.41. The DSS of claim 40, wherein the characteristics of the storagedevice are determined from one or more of: a manufacturer of the storagedevice; a manufacturer of a component of the storage device; a model ofthe storage device; a model of a component of the storage device; aserial number of the storage device; and a serial number of a componentof the storage device.
 42. The DSS of claim 40, wherein thecharacteristics of the storage device comprise input/output operationsper second (IOPS).
 43. The DSS of claim 35, wherein the calculation ofthe choking level comprises a combining of the plurality of congestioncontribution values according to a second determined function.
 44. TheDSS of claim 24, wherein the rate controller circuit is configured toprovide an application programming interface via which one or moresettings used by the rate controller circuit for the control the firstrate and the second rate are configurable during runtime of the ratecontroller circuit.
 45. The DSS of claim 24, wherein the rate controllercircuit is operable to: determine characteristics of hardware of theplurality of remote computing devices; perform an initial configurationof one or more settings used by the rate controller circuit for thecontrol the first rate and the second rate based on the characteristicsof the hardware; and adapt the one or more settings as requests areserviced and/or queued for servicing by the DSS.